Security Engineer, Detection and Response, San Francisco

Millions of people rely on Notion to do their most important work, and protecting that trust is foundational to everything we build. We’re looking for a hands-on Detection Engineer to build and operate the systems and workflows we use to detect and respond to attacks across Notion’s cloud-native environment. You’ll ship high-signal detections, improve the platform that powers them, participate in incident response, and help shape how detection and response engineering scales at Notion. You’ll work closely with Engineering, Corporate Security, and Infrastructure, with broad latitude to identify gaps, prioritize investments, and build what’s needed next. We view detection and response as a software engineering discipline: detections are code, platforms are products, and measurement matters

Responsibilities

Design and maintain high-signal detections across cloud, identity, endpoints, and SaaS environments; Build and improve the detection platform, including rule lifecycle management, tuning, measurement, and rollout safety; Develop tooling and automation that accelerate triage, enrichment, investigation, and detection authoring, including LLM-based workflows where useful; Translate threat intelligence and adversary TTPs into durable detections, telemetry requirements, and response improvements; Participate in investigations, incident response, and postmortems that drive long-term security improvements; Define and track key metrics such as coverage, MTTD, and alert quality to guide investment decisions; Participate in a shared on-call rotation for incident response

Requirements

Have 6+ years of experience in detection engineering, security operations, incident response, or threat hunting; Have built and operated production detections with strong signal quality and sustainable tuning processes; Are fluent in one or more detection languages such as Sigma, KQL, SPL, YARA-L, EQL, or Panther; Have an offensive security mindset and have led purple team, blue team, or adversary emulation exercises that improved detections and telemetry; Have strong cloud security experience in AWS, GCP, or Azure, including identity-focused attack detection; Are hands-on with SIEM, EDR, and SOAR platforms in large-scale environments; Communicate clearly through design docs, runbooks, and incident reports, and can drive projects independently

Nice to have

Experience applying LLMs or agent-style tooling to security workflows; Experience securing AI-enabled systems or endpoint tooling; Kubernetes or container detection experience; Background in threat intelligence, malware analysis, or digital forensics; Contributions to the detection engineering community through research, tooling, or talks; Experience at a high-growth startup or AI company

Benefits

Equity; Benefits